Download special issue of the ECMLPKDD 2015 journal track

Data Min Knowl Disc (2015) 29:1113–1115
DOI 10.1007/s10618-015-0431-0
Guest editors introduction: special issue of the
ECMLPKDD 2015 journal track
Concha Bielza1 · João Gama2 · Alípio Jorge2 ·
Indrė Žliobaitė3
Received: 3 July 2015 / Accepted: 6 July 2015 / Published online: 16 July 2015
© The Author(s) 2015
This special issue is a collection of papers submitted to the ECMLPKDD 2015 journal
track (and a few delayed from ECMLPKDD 2014) and accepted for publication in
Data Mining and Knowledge Discovery.
The European conference on machine learning and principles and practice of knowledge discovery in Databases, ECMLPKDD is a merger of the formerly independent
conferences ECML and PKDD.
ECMLPKDD first launched its journal track in 2013. The journal track initiative
had large adherence from the community. It was organized again in 2014 and 2015,
and will continue in 2016. Two reference journals are involved: Machine Learning
and Data Mining and Knowledge Discovery. In addition to being published in the
respective journal, papers were presented as regular papers in the conference. Thus,
all papers of this special issue were also presented by their authors at the ECMLPKDD
2015 conference in Porto, Portugal, from September 7th to 11th, 2015.
Responsible editor: Johannes Fuernkranz.
B
João Gama
[email protected]
Concha Bielza
[email protected]
Alípio Jorge
[email protected]
Indrė Žliobaitė
[email protected]
1
Technical University of Madrid, Madrid, Spain
2
University of Porto and INESC TEC, Porto, Portugal
3
Helsinki Institute for Information Technology HIIT, Aalto University, Espoo, Finland
123
1114
C. Bielza et al.
Table 1 Submissions statistics
Accepted
10
Rejected
84
Withdrawn
At authors for revision
Currently under review after revision
1
12
5
Currently under review 1st time
12
PAPERS RECEIVED (TOTAL)
124
Papers from 2014
4
In the journal track of this conference we look for high-quality submissions that
present original and mature work in the areas of data mining and machine learning.
However, given the special nature of a conference journal track, only papers that
naturally lend themselves to being presented were considered. These requirements
exclude, for example, journal versions of previously published conference papers as
well as survey papers, which were not considered for the special issue.
The possibility of successive resubmissions of improved versions of a paper has
a clear impact on the quality of the accepted papers. This way, the quality of the
conference increases to the benefit of participants and readers.
For the 2015 edition, we fostered the continuity of the submission process. The first
submission batch started on May 25, 2014, more than one year before the conference.
During one year and a half we received batches bi-weekly. Overall, 189 papers were
submitted (65 ML + 124 DAMI). As for Data Mining and Knowledge Discovery, at
the time of the deadline to send the papers for journal production, ten papers had been
accepted. Other 31 papers are still under review. If accepted, these papers will go to
the 2016 edition. Moreover, four papers accepted from the 2014 edition are included
in this year’s special issues. Table 1 summarizes the figures.
The papers included in this special issue of Data Mining and Knowledge Discovery reflect the current hot topics of knowledge discovery. They mostly cover network
analysis, clustering, regression and different mining tasks, like episode (set of events)
mining, visual data mining and graph mining. The approaches use different tools: partition models, dimensionality reduction, network evolution, directed acyclic graphs,
and even tensors. Data to be dealt with cover sequential data, range queries, dynamic
and harsh environments, preference data, Internet data and graphs that evolve over
time. Finally, applications or potential applications include biological networks and
sequences, community search, information cascades, vaccination campaign assessment and brain connectivity analysis.
Figure 1 presents a visual summary,1 in the form of a word cloud, generated from
the frequent words and bi-grams in the abstracts. Graphs and network analysis seem
to be the most relevant words.
This special issue would not have been possible without the help of many people.
In particular, we would like to thank the members of the ECMLPKDD 2015 Guest
1 Thanks to Carlos Ferreira.
123
Guest editors introduction: special issue of the ECMLPKDD…
1115
Fig. 1 Word cloud generated from the frequent words and bi-grams in the abstracts
Editorial board, as well as the additional referees for their hard work and timely
reviewing of the papers submitted to the special issue. A special thanks to the very
active reviewers, to the RAFT team and to Thanh Le Van for the editorial management
system.
123